Instructions to use lora-library/gustave-dore-dantes-inferno with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/gustave-dore-dantes-inferno with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/gustave-dore-dantes-inferno") prompt = "dantes_inferno" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
LoRA DreamBooth - gustave-dore-dantes-inferno
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on the instance prompt "dantes_inferno" using DreamBooth. You can find some example images in the following.
Test prompt: a honduran prison as depicted in dantes_inferno

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Model tree for lora-library/gustave-dore-dantes-inferno
Base model
runwayml/stable-diffusion-v1-5